In CMC we trust: the role of similarity

  • Authors:
  • Lauren E. Scissors;Alastair J. Gill;Kathleen Geraghty;Darren Gergle

  • Affiliations:
  • Northwestern University, Evanston, IL, USA;Northwestern University, Evanston, IL, USA;Northwestern University, Evanston, IL, USA;Northwestern University, Evanston, IL, USA

  • Venue:
  • Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
  • Year:
  • 2009

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Abstract

This paper examines how different forms of linguistic similarity in a text-chat environment relate to the establishment of interpersonal trust. Sixty-two pairs played an iterative social dilemma investment game and periodically communicated via Instant Messenger (IM). Novel automated and manual analysis techniques identify linguistic similarity at content, structural and stylistic levels. Results reveal that certain types of content (some positive emotion words, task-related words), structural (verb tense, phrasal entrainment), and stylistic (emoticons) similarity characterize high trusting pairs while other types of similarity (e.g., negative emotion words) characterize low trusting pairs. Contrary to previous literature, this suggests that not all similarity is good similarity.